Multi-cohort study in gastric cancer to develop CT-based radiomic models to predict pathological response to neoadjuvant immunotherapy.

ABSTRACT:

Background

Neoadjuvant immunotherapy has been shown to improve survival in patients with gastric cancer. This study sought to develop and validate a radiomics-based machine learning (ML) model for patients with locally advanced gastric cancer (LAGC), specifically to predict whether patients will achieve a major pathological response (MPR) following neoadjuvant immunotherapy. With its predictive capabilities, this tool shows promise for enhancing clinical decision-making processes in the future.

Methods

This study utilized a multicenter cohort design, retrospectively gathering clinical data and computed tomography (CT) images from 268 patients diagnosed with advanced gastric cancer who underwent neoadjuvant immunotherapy between January 2019 and December 2023 from two medical

SUBMITTER: Huang ZN 

PROVIDER: S-EPMC11934467 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature